Merge 98e6b30e29 into 50e0e3c70c

nerfstudio/data/utils/colmap_parsing_utils.py

@@ -399,7 +399,7 @@ def write_points3D_binary(points3D, path_to_model_file):
             write_next_bytes(fid, pt.id, "Q")
             write_next_bytes(fid, pt.xyz.tolist(), "ddd")
             write_next_bytes(fid, pt.rgb.tolist(), "BBB")
-            write_next_bytes(fid, pt.error, "d")
+            write_next_bytes(fid, float(pt.error.item()), "d")
             track_length = pt.image_ids.shape[0]
             write_next_bytes(fid, track_length, "Q")
             for image_id, point2D_id in zip(pt.image_ids, pt.point2D_idxs):

nerfstudio/plugins/registry.py

@@ -41,6 +41,11 @@ def discover_methods() -> t.Tuple[t.Dict[str, TrainerConfig], t.Dict[str, str]]:
     discovered_entry_points = entry_points(group="nerfstudio.method_configs")
     for name in discovered_entry_points.names:
         spec = discovered_entry_points[name].load()
+
+        # Support callable (function) entry points to avoid circular imports
+        if callable(spec):
+            spec = spec()
+
         if not isinstance(spec, MethodSpecification):
             CONSOLE.print(
                 f"[bold yellow]Warning: Could not entry point {spec} as it is not an instance of MethodSpecification"

nerfstudio/plugins/registry_dataparser.py

@@ -57,6 +57,11 @@ def discover_dataparsers() -> t.Tuple[t.Dict[str, DataParserConfig], t.Dict[str,
     discovered_entry_points = entry_points(group="nerfstudio.dataparser_configs")
     for name in discovered_entry_points.names:
         spec = discovered_entry_points[name].load()
+
+        # Support callable (function) entry points to avoid circular imports
+        if callable(spec):
+            spec = spec()
+
         if not isinstance(spec, DataParserSpecification):
             CONSOLE.print(
                 f"[bold yellow]Warning: Could not entry point {spec} as it is not an instance of DataParserSpecification"

nerfstudio/process_data/colmap_utils.py

@@ -64,16 +64,31 @@ def get_colmap_version(colmap_cmd: str, default_version: str = "3.8") -> Version
     return Version(default_version)
 
 
-def get_vocab_tree() -> Path:
+def get_vocab_tree(colmap_version: Version) -> Path:
     """Return path to vocab tree. Downloads vocab tree if it doesn't exist.
 
+    COLMAP switched from FLANN to faiss for vocabulary tree indexing in 3.12.0
+    (June 2025). FLANN- and faiss-based trees are mutually incompatible, so the
+    correct tree format is selected based on the detected COLMAP version, and
+    each format is cached under a distinct filename so that upgrading COLMAP
+    never silently serves a stale tree of the wrong format.
+
+    Args:
+        colmap_version: The detected COLMAP version, used to choose the tree format.
     Returns:
         The path to the vocab tree.
     """
-    vocab_tree_filename = Path(appdirs.user_data_dir("nerfstudio")) / "vocab_tree.fbow"
+    if colmap_version >= Version("3.12.0"):
+        vocab_tree_filename = Path(appdirs.user_data_dir("nerfstudio")) / "vocab_tree_faiss_words32K.bin"
+        vocab_tree_url = (
+            "https://github.com/colmap/colmap/releases/download/3.11.1/vocab_tree_faiss_flickr100K_words32K.bin"
+        )
+    else:
+        vocab_tree_filename = Path(appdirs.user_data_dir("nerfstudio")) / "vocab_tree.fbow"
+        vocab_tree_url = "https://demuc.de/colmap/vocab_tree_flickr100K_words32K.bin"
 
     if not vocab_tree_filename.exists():
-        r = requests.get("https://demuc.de/colmap/vocab_tree_flickr100K_words32K.bin", stream=True)
+        r = requests.get(vocab_tree_url, stream=True)
         vocab_tree_filename.parent.mkdir(parents=True, exist_ok=True)
         with open(vocab_tree_filename, "wb") as f:
             total_length = r.headers.get("content-length")
@@ -143,7 +158,7 @@ def run_colmap(
         f"--SiftMatching.use_gpu {int(gpu)}",
     ]
     if matching_method == "vocab_tree":
-        vocab_tree_filename = get_vocab_tree()
+        vocab_tree_filename = get_vocab_tree(colmap_version)
         feature_matcher_cmd.append(f'--VocabTreeMatching.vocab_tree_path "{vocab_tree_filename}"')
     feature_matcher_cmd = " ".join(feature_matcher_cmd)
     with status(msg="[bold yellow]Running COLMAP feature matcher...", spinner="runner", verbose=verbose):